Food Chemistry 213 (2016) 169–179

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Food Chemistry

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Accuracy of a method based on atomic absorption spectrometry todetermine inorganic arsenic in food: Outcome of the collaborative trialIMEP-41

http://dx.doi.org/10.1016/j.foodchem.2016.06.0330308-8146/� 2016 The Authors. Published by Elsevier Ltd.This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

⇑ Corresponding author.E-mail address: Maria.de-la-calle@ec.europa.eu (M.B. de la Calle).

I. Fiamegkos a, F. Cordeiro a, P. Robouch a, D. Vélez b, V. Devesa b, G. Raber c, J.J. Sloth d, R.R. Rasmussen d,T. Llorente-Mirandes e, J.F. Lopez-Sanchez e, R. Rubio e, F. Cubadda f, M. D’Amato f, J. Feldmann g, A. Raab g,H. Emteborg a, M.B. de la Calle a,⇑a European Commission, Joint Research Centre, Institute for Reference Materials and Measurements, 111 Retieseweg, 2440 Geel, BelgiumbMetal Contamination Laboratory (IATA-CSIC), Avd. Agustín Escardino 7, 46980 Paterna, Valencia, Spainc Institute of Chemistry, University of Graz, Universitätsplatz 1, 8010 Graz, Austriad Technical University of Denmark, National Food Institute, Division of Food Chemistry, Mørkhøj Bygade 19, 2860 Søborg, DenmarkeDepartment of Analytical Chemistry, University of Barcelona, Martí I Franque‘s 1-11, 08028 Barcelona, SpainfDepartment of Food Safety and Veterinary Public Health, Istituto Superiore di Sanità-Italian National Health Institute, Viale Regina Elena 299, 00161 Rome, Italyg Trace Element Speciation Laboratory (TESLA), University of Aberdeen, College of Physical Science, Chemistry, Meston Walk, Aberdeen AB24 3UE, Scotland, United Kingdom

a r t i c l e i n f o

Article history:Received 13 November 2015Received in revised form 22 March 2016Accepted 12 June 2016Available online 14 June 2016

Keywords:Inorganic arsenicCollaborative trialCerealsVegetablesMushroomsMusselsFishAlgae

a b s t r a c t

A collaborative trial was conducted to determine the performance characteristics of an analytical methodfor the quantification of inorganic arsenic (iAs) in food.The method is based on (i) solubilisation of the protein matrix with concentrated hydrochloric acid to

denature proteins and allow the release of all arsenic species into solution, and (ii) subsequent extractionof the inorganic arsenic present in the acid medium using chloroform followed by back-extraction toacidic medium. The final detection and quantification is done by flow injection hydride generation atomicabsorption spectrometry (FI-HG-AAS).The seven test items used in this exercise were reference materials covering a broad range of matrices:

mussels, cabbage, seaweed (hijiki), fish protein, rice, wheat, mushrooms, with concentrations rangingfrom 0.074 to 7.55 mg kg�1.The relative standard deviation for repeatability (RSDr) ranged from 4.1 to 10.3%, while the relative

standard deviation for reproducibility (RSDR) ranged from 6.1 to 22.8%.� 2016 The Authors. Published by Elsevier Ltd. This is anopenaccess article under the CCBY-NC-ND license

(http://creativecommons.org/licenses/by-nc-nd/4.0/).

1. Introduction

Arsenic (As) is a widely found contaminant, which occurs bothnaturally and as a result of human activities. Since the late 1960s,scientific evidence has been building up showing that exposure tohigh levels of inorganic As (iAs) may cause skin lesions with car-cinogenic (EPA, 2010; Hughes, Beck, Chen, Lewis, & Thomas,2011; National Research Council (NRC), 1999) or non-carcinogenic effects (U.S. Department of Health and humanservices, 2007; National Research Council, 2013). Based on theirchemical properties, arsenic species can be categorized as lipid-soluble or water-soluble arsenicals, the latter including both inor-ganic and organic compounds (Hajeb, Sloth, Shakibazadeh,

Mahyudin, & Afsah-Hejri, 2014). Inorganic arsenic species (As(III)and As(V)) seem to be the most toxic and carcinogenic forms(Muñoz, Vélez, & Montoro, 1999).

There is a worldwide concern about dietary iAs exposure andthe associated health risks have been emphasized in recent toxico-logical evaluations by the European Food Safety Authority (EFSA)and the Joint Expert Committee on Food Additives (JECFA) of theFood and Agriculture Organization of the United Nations/WorldHealth Organization (FAO/WHO) (EFSA, 2014; FAO JECFAMONOGRAPHS 8, 2011; WHO, 2011).

Until recently, most studies focused on the determination oftotal As in the diet (FDA, 2004). However, the recognition thatthe chemical form of As is critical for assessing risk, coupled withadvances in analytical methods, has resulted in a significant expan-sion of the amount of published scientific studies on As speciation(U.S. Department of Health and human services, 2007). The

Table 1List of reference materials used in the IMEP-41 exercise. S4, S7, S8 and pre-test areCRMs certified for total As. S7 and pre-test are also certified for iAs.

Sample ID Reference material Food commodity

S1 & S3 IMEP-107 RiceS2 IMEP-112 WheatS4 ERM-CE278k MusselsS5 IAEA-359 CabbageS6 IMEP-116 MushroomS7 NMIJ-7405a SeaweedS8 DORM-4 FishPre-test ERM-BC211 Rice

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determination of the iAs levels in food and the calculation of typi-cal intakes are critical to establish background exposure levels toiAs and to understand risks from excess intake of natural oranthropogenic sources (D’Amato et al., 2013; Lynch, Greenberg,Pollock, & Lewis, 2014). For this reason there has been an increas-ing interest in the development and validation of robust and reli-able methods to determine iAs in a range of food commodities.Such methods should support the introduction of maximum levelsfor iAs in rice and rice-derived products in the forthcoming revi-sion of Commission Regulation, (EC) 1881/2006 (2006).

The most commonly applied analytical methods for As specia-tion are based on high performance liquid chromatographyhyphenated with inductively coupled plasma mass spectrometry(HPLC-ICP-MS) (Francesconi & Kuehnelt, 2004; Maher et al.,2012). However, some drawbacks are associated with those meth-ods: HPLC-ICP-MS analytical platforms are expensive and notavailable in many routine control laboratories and furthermore,highly skilled analysts are needed, especially when matrices witha complex mixture of arsenic species are analysed as it is the casefor food items of marine origin. Other methods of analysis arebased on chemical separation of arsenic species with subsequentAAS determination (Rasmussen, Qian, & Sloth, 2013; Vieira et al.,2009). Hydride generation (HG) is one of the most straightforwardapproaches, with a high selectivity due to the formation of volatilehydrides of only few arsenic species (Musil et al., 2014;Pétursdóttir, Gunnlaugsdóttir, Krupp, & Feldmann, 2014). In gen-eral, methods based on HG-AAS are easier to implement and lesscostly than those based on HPLC-ICP-MS in terms of the analyticalinstrumentation needed.

In 2012 the European Committee for Standardization (CEN TC327/WG 4) standardised a method (EN 16278:2012) for the deter-mination of iAs in animal feeding stuffs by HG-AAS after micro-wave extraction and off-line separation of inorganic arsenic bysolid phase extraction (SPE) (BS EN-16278, 2012). This methodwas validated in a collaborative trial in the frame of the IMEP-32project (Sloth et al., 2011) and has furthermore been used in stud-ies on inorganic arsenic content in seafood and rice (Rasmussen,Hedegaard, Larsen, & Sloth, 2012; Rasmussen et al., 2013). Cur-rently, CEN TC 275/WG 10 is validating a method for the selectivedetermination of iAs in food based on HPLC-ICP-MS. Two otherstandard methods have been published, GB/T 5009.11-2003 (inChina) (EN 15517, 2008; GB/T5009.11, 2003), for the determina-tion of abio-arsenic in food and of iAs and in seaweed, respectively.Both methods are based on the selective determination of arsinefrom iAs under specific conditions without any previous separationof species and with final determination by atomic fluorescence(Chines standard) and by HG-AAS (CEN standard), respectively.However, IMEP-112 (de la Calle et al., 2012) (a proficiency testfor the determination of total and iAs in wheat, vegetable foodand algae) showed that the results obtained with those two stan-dards were strongly biased when applied to algae, a matrix witha complex pattern of arsenic species. Methylated species, such asdimethyl arsinic acid (DMA), abundant in samples of marine origin,can also generate volatile hydrides and could, therefore, interferein the determination of iAs and lead to positively biased results(Schmeisser, Goessler, Kienzl, & Francesconi, 2004).

Recently, the International Measurement Evaluation Program(IMEP), which is operated by the Joint Research Centre (JRC), aDirectorate General of the European Commission, organised a col-laborative trial (IMEP-41) for the validation of a method to deter-mine iAs in several foodstuffs. This method, which is based onthe selective extraction of iAs into chloroform and further determi-nation by HG-AAS, should serve as inexpensive complement to themethod being validated by CEN based on HPLC-ICP-MS. The stan-dard operating procedure (SOP) had been previously developed,in-house validated (Muñoz et al., 1999) and applied to the

determination of iAs in marine samples (Muñoz et al., 2000) bythe Trace Elements Group of the Institute of Agrochemistry andFood Technology (IATA) of the Spanish National Research Council(CSIC).

This manuscript summarises the outcome of IMEP-41 andincludes a discussion of problems associated with the selectivedetermination of iAs in food. The validated method will supportthe implementation of Regulation (EC) 1881/2006 setting maxi-mum levels for certain contaminants in foodstuffs, which in itsnext revision will include maximum levels (MLs) for iAs in riceand rice-derived products.

2. Collaborative study

2.1. Scope and principle of the method

The SOP (Fiamegkos et al. (2015)) can be downloaded from thewebpage of the Institute for Reference Materials and Measure-ments of the Joint Research Centre (JRC-IRMM) (https://ec.europa.eu/jrc/en/interlaboratory-comparisons). iAs is separated fromother arsenic species before being determined by flow injection-hydride generation-atomic absorption spectrometry (FI-HG-AAS).The extraction method is based on (i) solubilisation of the proteinmatrix with a high concentration of hydrochloric acid, which dena-tures the proteins and releases all the arsenic species, and (ii) thesubsequent selective extraction with chloroform of the iAs presentin the acid medium followed by back-extraction into acidic med-ium prior to analysis. The quantification limit of the method is0.010 mg kg�1 of iAs. When the method is run using the conditionsdescribed in the SOP, determination of iAs is free of the interfer-ences of other known arsenic species with the exception of mono-methyl arsonic acid (MA). However, this species is typically onlyfound as a minor arsenic species (Schoof & Yager, 2007).

2.2. Matrices tested in IMEP-41

The seven food commodities used in this collaborative trial arelisted in Table 1. Two of the distributed samples were identical (S1and S3, both rice) to ensure that the analysis of one sample doesnot affect the subsequent measurement on another sample. A ricepre-test sample (ERM-BC211) was sent to participants allowingthem to confirm the proper implementation of the method underinvestigation, before starting the collaborative trial.

2.3. Preparation of the test items

All the test items used in IMEP-41 were certified referencematerials (CRMs) or reference materials (RMs) previously used inIMEP proficiency tests; for this reason the test items underwent lit-tle processing for the purpose of the collaborative trial. The bottlesof the pre-test item and of the test items S1 (rice), S2 (wheat), S4(mussels) and S6 (mushroom) were relabelled to avoid the

I. Fiamegkos et al. / Food Chemistry 213 (2016) 169–179 171

identification of the test item by participants and expert laborato-ries. The new labels contained the appropriate code (IMEP-41,material number and sample number). For the test items S3 (rice),S7 (seaweed) and S8 (fish), the supplied units were opened, pooledinto a 5 L acid-washed plastic drum and placed in a 3D-mixer for30 min (Dynamix CM200, WAB, Basel, CH) for thorough mixingand re-homogenisation. The materials were then refilled inlabelled vials using a vibrating feeder and a balance in a clean-cell equipped with a HEPA filter. For cabbage (S5), a handful ofTeflon balls were added during mixing to break up agglomeratessince the material was clogged upon delivery. In order to breakthe agglomerates the material was forced to go through a500 lm mesh. It was then transferred into a 5 L acid-washed plas-tic drum and subsequently in a 3D-mixer for 30 min, before fillingin vials using a vibrating feeder and a balance in the clean-cell.

Care was taken to avoid cross-contamination between the dif-ferent materials and two powders were never handled at the sametime. Every material was mixed and filled only after thoroughcleaning of the whole equipment used.

2.4. Assigned values and associated uncertainties used to evaluate thetrueness of the method

In order to assess the trueness of the method, assigned valuesfor iAs mass fractions in all the test items were determined usingmethods of analysis different from the one under validation. TheiAs certified values and uncertainties in the ERM-BC211 pre-testitem and NMIJ-7405a (S7) (seaweed) were provided by the respec-tive CRM producers. The assigned value for the mushroom testitem (S6) was the one assigned during the PT IMEP-116, becausethat PT was run only some months before IMEP-41 and stabilityof the test item could be assumed. For the remaining samples theiAs mass fractions were determined by five expert laboratories,listed hereafter, selected on the basis of their demonstrated mea-surement capabilities in this field of analysis:

� Istituto Superiore di Sanità (Rome, Italy);� Institut für Chemie, Bereich Analytische Chemie, Karl-FranzensUniversität (Graz, Austria);

Table 2Analytical protocols, as described by the expert laboratories.

C1:Microwave assisted extraction was used to solubilize iAs. Samples (0.35 g) were mMicrowave irradiation was applied with the following temperature profile: 3 min ra95 �C, 30 min at 95 �C. The extracts were centrifuged (10 min, 8000 rpm, 4 �C) and tused, As(III) is converted to As(V), which appears as a well separated peak in themeasured as As(V), i.e., arsenate.

C2:About 0.5 g of powder was weighed with a precision of 0.1 mg into 50 mL polyprop1% (v/v) of a 30% H2O2 solution was added. Samples were extracted with a GFL-1095 �C for 60 min. After cooling to room temperature the extracts were centrifugedcentrifuged for 15 min at 8900 g. The supernatant was used directly for HPLC-ICP-

C3:For the determination of iAs subsamples of approximate 0.200 g were weighed inperoxide (Merck) was added. The solutions were placed in a water bath at 90 �C fcentrifuged at approximately 4000 rpm for 10 min and subsequently filtered (0.45anion exchange HPLC-ICP-MS. The method is currently being evaluated as a futur

C4A and C4B:0.1 g sample (by weight) were diluted with 10 g extraction solution containing 2%solution was mixed and heated (loosely capped) in a microwave oven for 50 min toto 75 �C, 5 min at 75 �C, ramp in 4 min to 95 �C, 30 min at 95 �C). The cooled solutioseparated from the residue. The supernatant for samples 4 and 8 was further dilutdilution of samples 4 and 8 was required due to excessive foaming of sample duringHPLC-ICP-MS. Two sets of data were delivered.

C5:The samples were accurately weighed in PTFE vessels and then extracted by addingsystem. The temperature was raised first to 55 �C (and held for 10 min) then to 75maintained for 30 min. Samples were cooled to room temperature and centrifugedsize 0.45 lm). Arsenic speciation was carried out in the extracts by LC-ICP-MS.

� Technical University of Denmark, National Food Institute – DTU(Søborg, Denmark);

� Department of Chemistry, University of Aberdeen (Aberdeen,UK);

� Department of Analytical Chemistry, Faculty of Chemistry,University of Barcelona (Barcelona, Spain)

Every expert laboratory received two bottles per test item withthe exception of S4 (mussels). For S4, due to lack of samples onlyone bottle could be included meaning that the same bottle shouldbe used for all analyses. Experts were requested to perform threeindependent measurements per bottle (under repeatability condi-tions) on two different days (one bottle/day) following the methodof their choice. They had to report the values obtained for the sixindependent measurements, the corresponding mean and its asso-ciated expanded measurement uncertainty (corresponding to a95% confidence interval). The five expert laboratories wereinformed about the type of food commodity contained in each bot-tle, because HPLC-based methods might need to be adapteddepending on the matrix to be analysed.

The analytical methods used by the expert laboratories aresummarized in Table 2. The order of these methods does not corre-spond to the list of expert laboratories given above. One of themanalysed the test items using two different techniques, based onHG-ICP-MS and HPLC-ICP-MS (C4A and C4B), respectively.

The mean of the means provided by the expert laboratories wasused, after removal of outliers, to derive the assigned values of thecollaborative trial (XCT), according to ISO Guide 35 (2006).

In all cases (except for S5 and S8) the expert laboratories reportedvalues with overlapping expanded measurement uncertainties,Fig. 1A–C, E and F. The uncertainty contribution due to characteriza-tion (uchar) was calculated according to ISO Guide 35 (2006).

uchar ¼ 1p

ffiffiffiffiffiffiffiffiffiffiffiffiXp

1

u2i

vuut ð1Þ

where ‘‘p” refers to the number of expert laboratories used to assignthe XCT, while ‘‘ui” is the associated combined standard measure-ment uncertainty reported by the experts.

ixed with 10 mL of 1% (v/v) HNO3 and 1% (v/v) H2O2 and left to stand overnight.mp to 55 �C, 10 min at 55 �C, 2 min ramp to 75 �C, 10 min at 74 �C, 2 min ramp tohe supernatants filtered through a 0.22 lm filter. With the extraction procedureanion exchange HPLC-ICP-MS chromatogram. Therefore inorganic arsenic was

ylene tubes, and a solution (10 mL) of 20 mmol L�1 trifluoracetic acid containing83 shaking water bath (Gesellschaft für Labortechnik, Burkwedel, Germany) atfor 15 min at 4700 g. An aliquot of 1 mL was transferred to Eppendorf vials andMS analysis.

to plastic tubes and 10.00 mL of 0.1 mol L�1 nitric acid (Merck) in 3% hydrogenor 60 min. Then the solutions were allowed to cool to room temperature andlm) prior to analysis. The determination of inorganic arsenic was done using

e European standard method by CEN.

(v/v) nitric acid and 3% (v/v) hydrogen peroxide in 50 mL Falcon tubes. Thetal (temperature program: ramp in 2 min to 50 �C, 5 min at 50 �C, ramp in 2 minn was weighed and then centrifuged at 4200 rpm for 10 min and the supernatanted by a factor of 5 and sample 7 by a factor of 10 using extraction solution. Thehydride generation. The solutions were then analysed by (A) HG-ICP-MS and (B)

10 mL of 0.2% (w/v) HNO3 and 1% (w/v) H2O2 solution in a microwave digestion�C (and held for 10 min) and finally the digest was taken up to 95 �C andat 3500 rpm for 12 min. The supernatant was filtered through PET filters (pore

Fig. 1. Measurement results of the expert laboratories (blue frame) and the CT participants. The blue dashed line corresponds to the mean of the respective results (XCT in thecase of the experts) and the red dashed lines the boundaries of the mean (XCT ± UCT, for the expert laboratories and Xobs ± 2SR for the participants of the CT). C⁄⁄, G⁄⁄ – Cochranand Grubbs outliers, C⁄ – Cochran straggler, (a) HPLC-ICP-MS chromatogram of standards, (b) HPLC-ICP-MS chromatogram of the test item (Provided by expert C2). (Forinterpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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In the case of S5 (cabbage) and S8 (fish), expert laboratoriesreported values, which did not overlap within their respectiveexpanded measurement uncertainties (Fig. 1.d and 1.g). uchar wasthen calculated according to ISO Guide 35:

uchar ¼ sffiffiffip

p ð2Þ

where ‘‘s” refers to the standard deviation of the means obtained bythe expert laboratories.

The uncertainties of the reference values (uCT) were then esti-mated combining the standard uncertainty of the characterization(uchar) with the contributions for homogeneity (ubb) and stability(ust) in compliance with ISO Guide 35.

uCT ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiu2char þ u2

bb þ u2st

qð3Þ

For S7 (seaweed), uCT was provided in the NMIJ certificate. Forthe former IMEP test items (S1 (rice), S2 (wheat), S6 (mushroom))ubb and ust were extracted from the corresponding IMEP reports toparticipants. As for the remaining samples (S4 (mussels), S5 (cab-bage), S8 (fish)) ubb and ust were derived from those reported fortotal As by the respective CRM producers.

The assigned values and their associated expandeduncertainties (XCT and UCT = 2 uCT) are presented in Table 3. In thecase of sample S7 (seaweed) the reference values of the CRM wereused.

Fig. 1 (continued)

I. Fiamegkos et al. / Food Chemistry 213 (2016) 169–179 173

2.5. Organisation of the collaborative trial

A call for participants was published on the JRC-IRMM web site(https://ec.europa.eu/jrc/en/interlaboratory-comparisons) and viathe network of National Reference Laboratories of the EuropeanUnion Reference Laboratory for Heavy Metals in Feed and Food(EURL-HM). Thirteen laboratories from nine European countriesregistered to this collaborative trial. The letter accompanying thesamples provided the general instructions for the participants,i.e., the measurand, type of samples, number of independent repli-cates required per bottle, detailed instructions on how to deter-mine the moisture content of the test items and the descriptionof the analytical method (SOP) to be used.

The measurand was defined as iAs in seven different foodmatri-ces. Laboratories were requested to perform three independent

measurements per bottle under repeatability conditions. This pro-cess was to be repeated on two different days (one bottle/day) fol-lowing the SOP. Laboratories were informed in the letteraccompanying the test item that the purpose of this collaborativetrial was to evaluate the method, not the analytical capabilitiesof the laboratory and that the SOP needed to be followed strictly.Any deviation of the SOP had to be reported to the organisers.

L05 failed to analyse correctly the pre-test item and L04 did notreport any results due to instrumentation failure. L06 modified theSOP and used ICP-MS instead of the prescribed HG-AAS; for thisreason the data submitted by this laboratory were excluded fromstatistical calculations. Ten participants reported compliant resultsthat were further evaluated.

Each participant received a package with sixteen bottles con-taining each approximately 20 g (S1 (rice) and S2 (wheat)), 8 g

Fig. 1 (continued)

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(S4 (mussels)), 5 g (S3 (rice), S5 (cabbage), S6 (mushroom), S7 (sea-weed) and S8 (fish)) of the test items (two bottles from each testitem), a bottle of the pre-test item (containing 15 g of material),a letter accompanying the samples, a ‘‘Confirmation of Receipts”and a copy of the SOP (Fiamegkos et al., 2015).

Dispatch was followed by the messenger’s parcel tracking sys-tem on the internet. Participants received an individual code toaccess the on-line reporting interface, to report their measurementresults and to complete the related questionnaire for collection ofrelevant information about the measurements and thelaboratories.

2.6. Statistical analysis

The statistical evaluation of data was performed following theinternational standard recommendations set by ISO 5725-2

(1994). The same statistical approach was used for the evaluationof the results reported by the expert laboratories.

The following sequence of statistical tests was applied:

i) Analysis of variance (ANOVA) to confirm that no statisticallysignificant difference existed, for any of the test items,between the two individual bottles provided to the partici-pants, analysed on different days. Since this was the case,all six replicated measurements were pooled for further cal-culations. This test could not be applied to the results of L07because this laboratory analysed only one bottle on one sin-gle day.

ii) Check for outliers in the laboratory precision (variance)applying the Cochran test. This test compares (for each testitem) the highest laboratory internal repeatability variancewith the sum of reported variances from all the participants;

Fig. 1 (continued)

Table 3Method performance characteristics from the collaborative study (following ISO 5725-2:1994 [22]).

Units S1 – Rice(IMEP-107)

S2 – Wheat(IMEP-112)

S4 – Mussels(ERM-CE278k)

S5 – Cabbage(IAEA-359)

S6 – Mushroom(IMEP-116)

S7 – Seaweed(CRM 7405a)

S8 – Fish(DORM-4)

N� Laboratories (afteroutlier rejection)

8 9 6 8 7 9 8

N� Outlier Lab (test used) 1 (C) – 1 (C), 1 (G) 1 (C) 2 (C) – 1 (C)N� Replicates excluded 6 – 11 6 12 – 6Assigned value

XCT ± UCT (k = 2)mg kg�1 0.108 ± 0.011 0.165 ± 0.021 0.086 ± 0.008 0.091 ± 0.016 0.321 ± 0.026 10.1 ± 0.5 0.27 ± 0.06

Overall meanXobs ± 2SR

mg kg�1 0.096 ± 0.030 0.146 ± 0.032 0.133 ± 0.048 0.074 ± 0.033 0.275 ± 0.034 7.548 ± 2.301 0.295 ± 0.134

Sr mg kg�1 0.007 0.015 0.011 0.007 0.011 0.357 0.030r mg kg�1 0.021 0.041 0.032 0.020 0.031 1.001 0.085RSDr % 7.8 10.1 8.6 9.6 4.1 4.7 10.3SR mg kg�1 0.015 0.016 0.024 0.016 0.017 1.151 0.067R mg kg�1 0.042 0.045 0.068 0.046 0.047 3.222 0.188RSDR % 15.6 10.9 18.2 22.1 6.1 15.2 22.8HorRat 0.71 0.52 0.83 1.02 0.32 1.29 1.18Recovery

Rec ± 2uRec (�95%)% 88.9 ± 29.4 88.7 ± 22.5 153.7 ± 57.6 81.6 ± 38.7 85.8 ± 12.6 74.7 ± 23.1 108.8 ± 55.4

C = Cochran test, G = Grubbs test (applied to laboratory means), GI = Grubbs internal test (applied to replicates within a laboratory).

Table 4List of identified outliers for the different matrices. ⁄⁄Notation in the figures.

Sample Laboratory (number ofoutlying results)

Outlier type⁄⁄

S1 – Rice (IMEP-107) L13 (6) CochranS4 – Mussels (ERM-CE278 k) C4A (6) Grubbs

C4B (6) GrubbsL08 (5) CochranL03 (6) Grubbs

S5 – Cabbage (IAEA-359) L13 (6) CochranS6 – Mushroom (IMEP-116) L08 (6) Cochran

L03 (6) CochranS8 – Fish (DORM-4) L03 (6) Cochran

I. Fiamegkos et al. / Food Chemistry 213 (2016) 169–179 175

iii) Check for laboratory outliers within the series of indepen-dent replicates applying the Grubbs-internal test (repeata-bility). This test is of particular relevance for laboratoriesbeing flagged as stragglers by the Cochran test;

iv) Check for outliers in the laboratory mean applying theGrubbs test. This test checks for laboratory means deviatingsignificantly from the overall mean (Xobs) calculated fromdata reported by all participants.

3. Results and evaluation

3.1. Method performance assessment

Trueness and precision of the method were estimated afteridentification and rejection (when applicable) of outliers. Table 4provides an overview of the identified outliers for all test items.

According to ISO 5725 outlying results should be investigatedand rejected only when an explanation is found for their anomaly.

Results should not be discarded only on the basis of statisticalanalysis.

Only the results reported by L03 for S4 (mussels) were flaggedas Grubbs outliers; all the others were Cochran outliers. The

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comments made by the laboratories in the questionnaire werescrutinised to understand the discrepancies of the results reportedfor some of the test items.

� L01 mentioned at the time of its registration that the instru-ment to be used for the analysis was old. It was not equippedwith a flow injection system and it needed to be operated inthe batch mode. The laboratory was not sure about the qualityof the results that could be obtained with this instrument. Thevery large scatter of reported results for all matrices confirmedthe laboratory’s concern. Hence, the results of L01 were notincluded in the statistical evaluation.

� The results reported by L07 for S4 (mussels) were identified asCochran outliers despite having an internal repeatability vari-ance comparable to that of other sets of data. This mathematicalartefact was due to the fact that the laboratory analysed onlyone bottle on one single day, thus having less degrees of free-dom. It was therefore decided to retain these results for furtherstatistical evaluation.

� L03 did not filter the chloroform phase after the first extraction.Filtering the chloroform phase is a crucial clean-up step neces-sary to avoid any traces of the HCl initially used to extract all Asspecies from the matrix (cf. Point 9.3 of the SOP) (Fiamegkoset al., 2015). Residues of the concentrated HCl in the chloroformphase may introduce a high contamination with organic arsenicspecies. Such a contamination would be particularly importantin samples in which iAs represents a small fraction of the totalAs, as it is frequently the case in samples of marine origin. Thiscould explain the high values reported by L03 for S4 (mussels)as well as the high dispersion of data for S8 (fish) and S6 (mush-room) (in this sample about half of the total As mass fractioncorresponds to organic compounds (Cordeiro et al., 2013)because the contamination is not necessarily constant in thedifferent replicates. L12, which did not filter the chloroformphase was not flagged as outlier for any of the test items, prov-ing that sound results can still be obtained when the organicphase is carefully sampled. Therefore, L03 was excluded fromthe statistical evaluation only when the results were flaggedas outliers.

L08 reported having many problems with S4 (mussels) and S8(fish), while L13 had problems with S5 (cabbage) and S8 due tothe formation of emulsion during the back extraction from chloro-form into 1 mol L�1 HCl (point 9.4 of the SOP). Laboratory L02 didnot apply the final filtration step 9.5.7 of the SOP which did nothave a significant influence on the reported results.

Regarding the results reported by the expert laboratories it isinteresting to mention that the results obtained by HG-ICP-MS(C4A) for S4 (mussels), S5 (cabbage) and S8 (fish) were not inagreement with the results reported by the experts using HPLC-ICP-MS within their respective expanded measurement uncertain-ties (corresponding to a 95% confidence level). Nevertheless, onlythe results reported by C4 (for both methods) for S4 were flaggedas Grubbs outliers. In addition the expert laboratory reported thatwhen analysing S4 and S8 the extracts had to be diluted to avoidformation of foam during hydride generation. Foam generationduring HG-ICP-MS was most likely resulting from the high proteincontent of these samples. Extraction of samples using 2% (v/v)nitric acid and 3% hydrogen peroxide does not destroy the proteinmatrix and since no further purification of the solutions took placesolubilised proteins can react with sodium borohydride leading tostrong foam formation.

All the remaining measurement results were used to evaluatethe trueness and precision of the method under validation. Table 3provides for each sample:

� the number of laboratories used to assess the performancecharacteristics of the method (after outlier exclusion);

� the number of outlier laboratories and replicates;� the assigned values and associated expanded measurementuncertainties (XCT, UCT);

� the overall observed mean (after the outlier rejection, Xobs) andtheir respective expanded uncertainty, expressed as the repro-ducibility standard deviation (SR) multiplied by a coverage fac-tor of 2, to approximate a 95% confidence interval;

� the repeatability standard deviation (Sr) the repeatability limit r(computed as 2.8 Sr) and the repeatability relative standarddeviation, or within-laboratory variability, (RSDr);

� the reproducibility standard deviation (SR), the reproducibilitylimit R (computed as 2.8 SR) and the RSDR;

� the Horwitz ratio (HorRat) expressed as the ratio between theobserved RSDR value divided by the predicted reproducibilityrelative standard deviation (PRSDR) value calculated from theHorwitz equation (Thompson, 2000); and

� the overall analytical recovery R, is calculated as:

R ¼ 100Xobs

XCTð4Þ

while the associated uncertainty (uR) is estimated as [29]:

uR ¼ R

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiuobs

Xobs

� �2

þ uCT

XCT

� �2s

ð5Þ

Where: uobs is the estimated standard deviation under repro-ducibility conditions (SR),uCT is the standard uncertainty associated to the XCT.

No statistically significant difference could be identifiedbetween the overall observed mean and the assigned values forall test items when taking into account the estimated expandeduncertainty of the analytical recovery (2uR, to approximate the95% confidence interval). Therefore, no significant bias could beidentified for the matrices investigated.

Consequently, the method is considered fit for its intended pur-pose, since the HorRat ratios are below 2 in all cases.

No significant difference was observed for the two identicalsamples (S1 and S3, both rice), where the following ranges(expressed as Xobs ± 2 SR) were obtained: 0.096 ± 0.030 mg kg�1

for S1 and 0.089 ± 0.022 mg kg�1 for S3.

3.2. Degree of difficulty in the determination of iAs mass fraction indifferent types of matrices

An evaluation of the results and of the comments reported bythe participants in IMEP-41 on the method under validation, andby the expert laboratories using the method of their choice, madeit possible to extract some conclusions about the inherent diffi-culty of iAs determination in different types of matrices. Twomajorclusters could be identified: 1) matrices of marine origin, and 2)matrices of non-marine origin.

3.2.1. Matrices of marine originThe selective determination of iAs seems to be particularly chal-

lenging in food of marine origin: mussels (S4), seaweed (S7) andfish (S8). In those samples iAs represents only a small fraction ofthe total As mass fraction (Fig. 1C, F and G). Samples of marine ori-gin contain often a very large number of different As-species, someof which may form also volatile hydrides which can interfere withthe determination of iAs by HG-AAS or HG-ICP-MS, and for HPLC-ICP-MS there is always the risk of co-eluting species. This is partic-ularly true in the case of S4 (mussels) and S8 (fish), where the iAs

I. Fiamegkos et al. / Food Chemistry 213 (2016) 169–179 177

mass fractions (0.086 ± 0.008 mg kg�1 and 0.27 ± 0.06 mg kg�1,respectively), represent 1 and 4% of the total As mass fraction(6.7 ± 0.4 mg kg�1 in S4 and 6.80 ± 0.64 mg kg�1 in S8). Seaweeds(S7) typically also contain high levels of several organic arsenicspecies, but in this sample the iAs mass fraction(10.1 ± 0.5 mg kg�1) represents 28% of the total As mass fraction(35.8 ± 0.9 mg kg�1).

As discussed before, several laboratories (L03, L08 and L13) hadproblems with the analysis of S4 (mussels) and/or S8 (fish), andreported results which were either biased or characterised by alarge dispersion. The same difficulties were observed in the popu-lation of expert laboratories although only the results reported byexpert C4 (for both methods: HG-ICP-MS and HPLC-ICP-MS) for S4,were flagged as Grubbs outliers. This expert reported that ‘‘S4 con-tains an organic As-compound eluting very near to As(V), which mayco-elute with As(V) depending on column conditions used”. If thatcompound could also generate the hydride, it would explain theresults obtained by this laboratory for S4, using the two differenttechniques, for which the results are in good agreement.

The results reported for S4 (mussels) by the participants inIMEP-41 using the method under validation are systematicallyhigher than the assigned value, although still overlapping with itwithin their respective expanded uncertainties. Bivalves areknown to contain MA (Schoof & Yager, 2007). In the samples anal-ysed by Muñoz et al. (2000), MA did not exceed 0.4% of the total Asmass fraction in any sample. The content of MA in S4 (data pro-vided by expert C2) is 0.183 ± 0.003 mg kg�1 (expressed as As), cor-responding to 3% of total As. The MA mass fraction in this test itemis therefore high and could explain the results reported for iAs inIMEP-41, because as indicated before, MA can interfere in thedetermination of iAs in the method being validated. The high con-tent of MA in S4 could also be a feasible explanation for the highresult reported by C4 using HG-ICP-MS but not the result obtainedusing HPLC-ICP-MS because this expert laboratory confirmed thatco-elution of MA and As(V) did not occur under the conditionsused. The high value obtained by C4 for S4 must be due to theinterference of some unknown As species.

However, since: 1) the method under validation does not per-form differently that other methods, 2) the reference value, calcu-lated out of the values reported by experts, is included in the rangecovered by the results obtained by the participants in the collabo-rative trial (95% confidence interval) and 3) the HorRat value forthis matrix (0.83) falls in the accepted range 0.5–2, we considerthat the method is fit for the purpose of determining iAs inbivalves. In addition the validated method does not imply interpre-tation of the complex chromatograms obtained by HPLC-ICP-MSwhere the inorganic arsenic peak could be hidden/enhanced ifproper separation is not achieved.

As mentioned before, some laboratories encountered also someproblems in the determination of iAs in S8 (fish), due to the forma-tion of an emulsion. Also expert C4 reported that ‘‘S8 producedhighly divergent results between HPLC and HG-ICP. The samples havebeen done several times with the same results; the reason for this isnot clear”. Indeed, the results obtained by C4 using HG-ICP-MS(C4A) were twice as high as the result obtained by the same labo-ratory using HPLC-ICP-MS (C4B), and were not in agreement withany of the results reported using HPLC-ICP-MS, within their respec-tive uncertainties. Nevertheless, C4A was not flagged as an outlierfor S8. Although the mean of the results reported for S8 by the par-ticipants in IMEP-41 is in good agreement with the assigned value,it has to be mentioned that the standard uncertainties associatedto the assigned value and to the mean of the participant’s resultsfor S8 are the largest among all the matrices included in the valida-tion (Table 3) showing the difficulties experienced with the analy-sis of this specific sample.

The results reported for S7 (seaweed, Sargassum fusiforme, syn.hizikia-fusiforme) by the two populations, experts and participantsin the collaborative trial, deserve some in-depth discussion. Thereis quite a good agreement within each of the two populations,being the standard uncertainties associated to the assigned valueand to the mean of results reported by the participants 2.5 and15%, respectively. However, the recovery obtained for S7 with themethod under validation is the lowest among all the test items:75%. Several arguments can be provided to try to explain this fact:

� Due to the high iAs mass fraction in S7 (seaweed), about twoorders of magnitude higher than those in the other test items,laboratories had to dilute the final extract (1:4 to 1:25 dilutionfactors were applied) to be able to use the calibration curve con-structed following the SOP, introducing in this way an addi-tional error in the final calculation. The dilution bias might becaused by a systematic dilution error, by a change in the matrixeffect in the diluted extract and/or by substraction of a reagentcontribution to the blank without taking into consideration thedilution factor.

� Arsenosugars are the major arsenic compounds in marine algae(Schmeisser et al., 2004). Hijiki contains about 50% arsenosug-ars which can be changed or completely destroyed by heatingor acid treatment (Narukawa et al., 2012). S7 (seaweed) is a cer-tified reference material in which the As(V) mass fraction hasbeen certified on the basis of results obtained with HPLC-ICP-MS and ion chromatography (IC)-ICP-MS, using two differentextraction methods and with water as extractant: ultrasonica-tion (for 1 h) and microwave assistance (for 30 min), in bothcases at 60 �C. Under those conditions and according to theCRM producers (Narukawa et al., 2012), arsenosugars wouldnot be changed or destroyed, what would have resulted in anoverestimation of iAs.In the method being validated in IMEP-41, the extraction isbased on: 1) solubilisation of the protein matrix with 6 mol L�1

HCl at room temperature shaking for 15 min with a mechanicalshaker and leaving then the mixture to rest for 12–15 h, 2) sub-sequent extraction with chloroform of the iAs present in theacid medium, shaking for 5 min with a mechanical shaker.

� In the method being validated only extracted species capable ofgenerating hydrides would be detected using atomic absorptionspectrometry, contrary to what would happen when usingICP-MS. The high temperatures reached in the ICP torchwould atomise and ionise any arsenic species (including theorganic species, such as arsenosugars), which under certainchromatographic conditions could co-elute with As(V). In thesame paper the authors succeeded to generate volatile arsenichydride from arsenosugars, although the mechanism of reactioncould not be clarified.

The chance that the results obtained by all expert laboratoriesworking under different extraction conditions would have beenaffected by the same interference or by inter-conversion of specieswith the same extent is rather low. For this reason the explanationprovided in the first bullet point (dilution necessary) seems moreplausible.

3.2.2. Matrices of non-marine originFour test items of non-marine origin were included in this

collaborative trial, namely plants/funghi: Rice (S1), wheat (S2),cabbage (S5) and mushrooms (S6).

The simplest matrix regarding distribution pattern of arsenicspecies, was wheat (S2) where only iAs was detected. In the ricetest item (S1) the major arsenic species was iAs, followed byDMA and some traces of MA. The pattern was slightly more

178 I. Fiamegkos et al. / Food Chemistry 213 (2016) 169–179

complex in mushrooms (S6) where not only iAs, DMA andMAwerepresent but also some other non-identified As compounds.

The more challenging matrix in the group of non-marine testitems was cabbage (S5): in the chromatogram obtained by expertC2 for this test item (Fig. 1.D) two peaks can be observed, one cor-responding to iAs and a second non-identified compound. The dis-persion of results reported for S5 was the second largest after fish(S8) for both populations, expert laboratories and participants inIMEP-41, with 17.6% and 44.6% expanded standard uncertaintiesassociated to the assigned values and to the overall mean of thecollaborative trial, respectively. Very likely the non-identifiedarsenic species is able to generate a volatile hydride to someextent, which would explain the results obtain by expert C4 usingHG-ICP-MS. Although not flagged as outlier, those results (C4A) donot overlap with any of the results obtained by the expert labswhen using HPLC-ICP-MS. Also L13 reported problems with S5due to the formation of an emulsion during the back extractionfrom chloroform into diluted HCl, which would explain the largedispersion of results reported by L13.

The determination of iAs in cereals seems to be more straight-forward than in other food of plant origin and for these sampletypes good agreement between the results obtained by expert lab-oratories and participants was obtained.

4. Conclusions

The trueness and precision of a method for the determination ofiAs in a broad range of food commodities has been assessed bymeans of a collaborative trial. The method does not imply theuse of sophisticated/expensive instrumentation and can be imple-mented, even in challenging matrices. Marine matrices were par-ticularly challenging although the requirements of internationalguidelines for validation of methods were met. For instance prob-lems in the determination of iAs in bivalves were encountered byparticipants when using the method under validation and by oneof the experts applying two different methods: direct hydride gen-eration –ICP-MS and by HPLC-ICP-MS. In this sense it could bequestioned if it is possible to determine iAs in bivalves using anyanalytical approach because unknown arsenic species may inter-fere depending on the conditions and method of analysis used.

The proposed method can be used to monitor iAs in food andhelps in providing more data on the fraction of As with the highesttoxicity in the human diet. Such data are strongly needed for refin-ing risk assessment of human dietary exposure to iAs.

The main drawback of the method is that it implies the use ofsuch an organic solvent as chloroform.

Moreover, this exercise, including the results reported by theparticipants of the collaborative trial and by expert laboratoriesusing HPLC-ICP-MS based methods, reveals the difficulty of deter-mining iAs in food of marine origin and that any method to be usedfor that purpose needs to be properly validated and/or imple-mented by the control laboratories.

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